• Title/Summary/Keyword: Time Warping

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Contents based digital audio retrieval using the Dynamic Time Warping Technique (Dynamic Time Warping 기법을 이용한 내용기반 디지털 오디오 검색)

  • Sung, Bo-Kyung;Ko, Il-Ju
    • 한국HCI학회:학술대회논문집
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    • 2007.02a
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    • pp.287-292
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    • 2007
  • 최근 다양한 분야에서(웹 포털, 유료 음원서비스 등) 디지털 오디오의 검색이 사용되고 있다. 이러한 분야에서 디지털 오디오의 검색은 디지털 오디오 데이터가 가지고 있는 자체 메타 정보를 이용하여 이루어진다. 하지만 메타 정보가 다르게 작성 되었거나 작성되지 않은 경우 정확한 검색은 어렵다. 요즘 이러한 문제의 보완 방안으로 내용기반 정보 검색 기법을 이용한 검색이 이루어지고 있다. 본 논문에서는 내용 기반 디지털 오디오 검색 방법에 대해 논하고자 한다. 내용기반으로 디지털 오디오를 검색하기 위해 음성 인식 문야에서 유사도 측정에 사용하는 Dynamic Time Warping 기법을 활용하여 디지털 오디오 간의 유사도 측정을 하였다. 제안된 유사도 측정을 통한 내용기반 디지털 오디오검색 방법의 검증을 위해 같은 장르에서 무작위 추출된 100곡에서 시행한 90번의 검색은 모두 성공했다. 검색에 사용된 90개의 디지털 오디오는 10개의 디지털 오디오를 압축방식과 비트율을 다르게 조합하여 만들었다.

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Time Series Pattern Recognition based on Branch and Bound Dynamic Time Warping (분기 한정적인 동적 타임 워핑 기반의 시계열 패턴인식)

  • Jang, Seok-Woo;Park, Young-Jae;Kim, Gye-Young
    • Journal of KIISE:Software and Applications
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    • v.37 no.7
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    • pp.584-589
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    • 2010
  • The dynamic time warping algorithm generally used in time series pattern recognition spends most of the time in generating the correlation table, and it establishes the global path constraint to reduce the corresponding time complexity. However, the constraint restrains just in terms of the time axis, not considering the contents of input patterns. In this paper, we therefore propose an efficient branch and bound dynamic time warping algorithm which sets the global constraints by adaptively reflecting the patterns. The experimental results show that the proposed method outperforms conventional methods in terms of the speed and accuracy.

Warping of 2D Facial Images Using Image Interpolation by Triangle Subdivision (삼각형 반복분할에 의한 영상 보간법을 활용한 2D 얼굴 영상의 변형)

  • Kim, Jin-Mo;Kim, Jong-Yoon;Cho, Hyung-Je
    • Journal of Korea Game Society
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    • v.14 no.2
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    • pp.55-66
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    • 2014
  • Image warping is a technology to transform input images to be suitable for given conditions and has been recently utilized in changing face shape of characters in the field of movies or animation. Mesh warping which is one of warping methods that change shapes based on the features of face forms warping images by forming rectangular mesh groups around the eyes, nose, and mouth and matching them 1:1. This method has a problem in the resultant images are distorted in the segments of boundaries between meshes when there are errors in mesh control points or when meshes have been formed as many small area meshes. This study proposes a triangle based image interpolation technique to minimize the occurrence of errors in the process of forming natural warping images of face and process accurate results with a small amount of arithmetic operation and a short time. First, feature points that represent the face are found and these points are connected to form basic triangle meshes. The fact that the proposed method can reduce errors occurring in the process of warping while reducing the amount of arithmetic operation and time is shown through experiments.

A Technology Analysis Model using Dynamic Time Warping

  • Choi, JunHyeog;Jun, SungHae
    • Journal of the Korea Society of Computer and Information
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    • v.20 no.2
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    • pp.113-120
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    • 2015
  • Technology analysis is to analyze technological data such as patent and paper for a given technology field. From the results of technology analysis, we can get novel knowledge for R&D planing and management. For the technology analysis, we can use diverse methods of statistics. Time series analysis is one of efficient approaches for technology analysis, because most technologies have researched and developed depended on time. So many technological data are time series. Time series data are occurred through time. In this paper, we propose a methodology of technology forecasting using the dynamic time warping (DTW) of time series analysis. To illustrate how to apply our methodology to real problem, we perform a case study of patent documents in target technology field. This research will contribute to R&D planning and technology management.

Real-Time Simulation of Thin Rod

  • Choi, Min Gyu;Song, Oh-Young
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.7 no.4
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    • pp.849-859
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    • 2013
  • This paper proposes a real-time simulation technique for thin rods undergoing large rotational deformation. Rods are thin objects such as ropes and hairs that can be abstracted as one-dimensional structures. Development of a real-time physical model that can produce visually convincing animation of thin rods has been a challenging problem in computer graphics. We adopt continuum mechanics to formulate the governing equation, and develop a modal warping technique for rods to integrate the governing equation in real-time; This is a novel extension of the previous modal warping techniques developed for solids and shells. Experimental results show that the proposed method runs in real-time even for large meshes and it can simulate large bending and/or twisting deformations.

Fault Detection and Identification of Induction Motors with Current Signals Based on Dynamic Time Warping

  • Bae, Hyeon;Kim, Sung-Shin;Vachtsevanos, George
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.7 no.2
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    • pp.102-108
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    • 2007
  • The issues of preventive and condition-based maintenance, online monitoring, system fault detection, diagnosis, and prognosis are of increasing importance. This study introduces a technique to detect and identify faults in induction motors. Stator currents were measured and stored by time domain. The time domain is not suitable for representing current signals, so wavelet transform is used to convert the signal; onto frequency domain. The raw signals can not show the significant feature, therefore difference values are applied. The difference values were transformed by wavelet transform and the features are extracted from the transformed signals. The dynamic time warping method was used to identify the four fault types. This study describes the results of detecting fault using wavelet analysis.

Fault Detection and Diagnosis of Faulty Bearing and Broken Rotor Bar of Induction Motors Based on Dynamic Time Warping (DTW를 이용한 유도전동기 베어링 및 회전자봉 고장진단)

  • Lee, Jae-Hyun;Bae, Hyeon
    • Journal of Advanced Marine Engineering and Technology
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    • v.31 no.1
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    • pp.95-102
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    • 2007
  • The issues of preventive and condition-based maintenance, online monitoring, system fault detection, diagnosis and prognosis are of increasing importance. This study introduces a technique to detect and identify faults in induction motors. Stator currents were measured and stored by time domain. The time domain is not suitable for representing current signals, so wavelet transform is used to convert the signals onto frequency domain. The raw signals can not show the significant feature, therefore difference values between the signal of the health conditions and that of the fault conditions are applied. The difference values were transformed by wavelet transform and the features are extracted from the transformed signals. The dynamic time warping method was used to identify the fault type. This study describes the results of detecting fault using wavelet analysis.

An Index-Based Approach for Subsequence Matching Under Time Warping in Sequence Databases (시퀀스 데이터베이스에서 타임 워핑을 지원하는 효과적인 인덱스 기반 서브시퀀스 매칭)

  • Park, Sang-Hyeon;Kim, Sang-Uk;Jo, Jun-Seo;Lee, Heon-Gil
    • The KIPS Transactions:PartD
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    • v.9D no.2
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    • pp.173-184
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    • 2002
  • This paper discuss an index-based subsequence matching that supports time warping in large sequence databases. Time warping enables finding sequences with similar patterns even when they are of different lengths. In earlier work, Kim et al. suggested an efficient method for whole matching under time warping. This method constructs a multidimensional index on a set of feature vectors, which are invariant to time warping, from data sequences. For filtering at feature space, it also applies a lower-bound function, which consistently underestimates the time warping distance as well as satisfies the triangular inequality. In this paper, we incorporate the prefix-querying approach based on sliding windows into the earlier approach. For indexing, we extract a feature vector from every subsequence inside a sliding window and construct a multidimensional index using a feature vector as indexing attributes. For query processing, we perform a series of index searches using the feature vectors of qualifying query prefixes. Our approach provides effective and scalable subsequence matching even with a large volume of a database. We also prove that our approach does not incur false dismissal. To verify the superiority of our approach, we perform extensive experiments. The results reveal that our approach achieves significant speedup with real-world S&P 500 stock data and with very large synthetic data.

An Effective Similarity Search Technique supporting Time Warping in Sequence Databases (시퀀스 데이타베이스에서 타임 워핑을 지원하는 효과적인 유살 검색 기법)

  • Kim, Sang-Wook;Park, Sang-Hyun
    • Journal of KIISE:Databases
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    • v.28 no.4
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    • pp.643-654
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    • 2001
  • This paper discusses an effective processing of similarity search that supports time warping in large sequence database. Time warping enables finding sequences with similar patterns even when they are of different length, Previous methods fail to employ multi-dimensional indexes without false dismissal since the time warping distance does not satisfy the triangular inequality. They have to scan all the database, thus suffer from serious performance degradation in large database. Another method that hires the suffix tree also shows poor performance due to the large tree size. In this paper we propose a new novel method for similarity search that supports time warping Our primary goal is to innovate on search performance in large database without false dismissal. to attain this goal ,we devise a new distance function $D_{tw-Ib}$ consistently underestimates the time warping distance and also satisfies the triangular inequality, $D_{tw-Ib}$ uses a 4-tuple feature vector extracted from each sequence and is invariant to time warping, For efficient processing, we employ a distance function, We prove that our method does not incur false dismissal. To verify the superiority of our method, we perform extensive experiments . The results reveal that our method achieves significant speedup up to 43 times with real-world S&P 500 stock data and up to 720 times with very large synthetic data.

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Feature-Strengthened Gesture Recognition Model based on Dynamic Time Warping (Dynamic Time Warping 기반의 특징 강조형 제스처 인식 모델)

  • Kwon, Hyuck Tae;Lee, Suk Kyoon
    • KIPS Transactions on Software and Data Engineering
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    • v.4 no.3
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    • pp.143-150
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    • 2015
  • As smart devices get popular, research on gesture recognition using their embedded-accelerometer draw attention. As Dynamic Time Warping(DTW), recently, has been used to perform gesture recognition on data sequence from accelerometer, in this paper we propose Feature-Strengthened Gesture Recognition(FsGr) Model which can improve the recognition success rate when DTW is used. FsGr model defines feature-strengthened parts of data sequences to similar gestures which might produce unsuccessful recognition, and performs additional DTW on them to improve the recognition rate. In training phase, FsGr model identifies sets of similar gestures, and analyze features of gestures per each set. During recognition phase, it makes additional recognition attempt based on the result of feature analysis to improve the recognition success rate, when the result of first recognition attempt belongs to a set of similar gestures. We present the performance result of FsGr model, by experimenting the recognition of lower case alphabets.